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Title:S-index: Towards Better Metrics for Quantifying Research Impact

Abstract: The ongoing growth in the volume of scientific literature available today
precludes researchers from efficiently discerning the relevant from irrelevant
content. Researchers are constantly interested in impactful papers, authors and
venues in their respective fields. Moreover, they are interested in the
so-called recent "rising stars" of these contexts which may lead to attractive
directions for future work, collaborations or impactful publication venues. In
this work, we address the problem of quantifying research impact in each of
these contexts, in order to better direct attention of researchers and
streamline the processes of comparison, ranking and evaluation of contribution.
Specifically, we begin by outlining intuitive underlying assumptions that
impact quantification methods should obey and evaluate when current
state-of-the-art methods fail to satisfy these properties. To this end, we
introduce the s-index metric which quantifies research impact through influence
propagation over a heterogeneous citation network. s-index is tailored from
these intuitive assumptions and offers a number of desirable qualities
including robustness, natural temporality and straightforward extensibility
from the paper impact to broader author and venue impact contexts. We evaluate
its effectiveness on the publicly available Microsoft Academic Search citation
graph with over 119 million papers and 1 billion citation edges with 103
million and 21 thousand associated authors and venues respectively.